Category Archives: Plant Health

Agronomy, AgTech, Automation, Conference, Data Analytics, Drainage, events, Membership, MicroFarm, Nutrients, Orcharding, Plant Health, Precision Agriculture, Projects, Research, Robotics, Sensing, Soil, viticulture

LandWISE 2018 Conference Sponsors

We are delighted to present our 2018 Platinum Sponsors, BASF Crop Protection, Hawke’s Bay Regional Council and Power Farming.

BASF Crop Protection and  Hawke’s Bay Regional Council are long term loyal supporters of LandWISE and their contributions are highly valued. Power Farming is a new Platinum Sponsor in 2018 and we look forward to our relationship with them. AGMARDT sponsored our international speakers.

 Hawke’s Bay Regional Council has been part of LandWISE since 1999, when some farmers, scientists and industry people got together to try and improve soil quality, stop wind erosion and improve irrigation efficiency and of course yields. Our Mission doesn’t change so much, but the tools to help us along the way certainly have!

BASF Crop Protection has been a foundation sponsor of the LandWISE MicroFarm as well as our annual conferences.  They show ongoing enthusiasm to help us help farmers and that is greatly appreciated.

Our new Platinum Sponsor is Power Farming. We’ve had help from them in several of our projects, most recently with the Canterbury field work and field events that were part of our FAR/SFF Fertiliser Spreader Calibration project.  The Power Farming catalogue matches well with our conference delegates’ and members’ interests.

We are grateful to our long-term Gold Sponsors, Horizons Regional Council, Process Vegetables NZ and Vegetables NZ, and AGMARDT.

Horizons Regional Council has supported our conference field sessions for a number of years and is a key partner for some of our major research and extension projects including “Integrated Storm Water Management” and “Holding it Together“.

AGMARDT has funded travel expenses to bring many international speakers to our Annual Conferences, as well as several projects including “Soils First Farmers” and “Validating Field Robotics“.

Process Vegetables NZ and Vegetables NZ have been conference sponsors for many years. As the levy funded industry research bodies they represent the farmers in our membership and nationally. These bodies also co-fund research projects including a number of our Sustainable Farming Fund initiatives.

Our conference delegates are well supported by our meal sponsors and trade displays. In addition, Apatu Farms sponsor high school students to attend, and McCain Foods and Heinz-Wattie’s are sponsoring keynote Sarah Pethybridge‘s travel.  Thanks everyone!

 

Agronomy, Conference, events, LandWISE People, Nutrients, Plant Health, Soil, Water, Weeds

Dan Drost

Leave a comment

Professor Daniel Drost is a vegetable researcher and extension specialist from Utah State University.

Dan Drost grew up on a small diversified animal and crop farm in Michigan (USA). He graduated from Michigan State University with a BS and MS degree in Horticulture. In 1983, he moved to New Zealand to teach Horticulture at Massey University. He returned to the US in 1987 to study at Cornell University where he was awarded a PhD in 1991 in Vegetable Crops and Plant Physiology. 

Dan’s research and outreach efforts focus on small intensive production systems, sustainable and organic agriculture, and how land-use management impacts field and farm scale productivity. In his 25 years at Utah State, he has authored more than 150 extension and scientific articles on vegetable production and management practices, shared his understanding of farming systems with producers, scientists and industry leaders around the world, and focused his attention on sustainable vegetable cropping systems that are farm appropriate, socially acceptable, and economically viable.

One of our invited international keynote speakers, Dan was bought to New Zealand in conjunction with Onions NZ and Plant & Food Research to discuss sustainable production systems. His presentation to LandWISE 2018 was titled “Sustainable Crop Production: Field and Farmscape Management for Sustainability”.

Dan says,

“Insects, diseases, nutrient management, and weeds pose yearly threats to vegetable productivity and sustainability. This presentation will address how to best manage the farmscape (whole farm) to protect and mitigate these risks in field and farm settings. Using examples from a variety of vegetable crops (annuals, perennials, intensively managed) grown in a range of settings, I will outline how modern farms adapt to and deal with yearly uncertainty.“

Dan and colleagues have completed a lot of work on high tunnels for crop production. See a video here.

You can hear and discuss sustainable production with Dan at LandWISE 2018 in Havelock North on 23-24 May.

 

 

Dan’s attendance at LandWISE 2018 was supported by AGMARDT

Conference, LandWISE People, Plant Health, Precision Agriculture, Research, Sensing

Taylor Welsh

Leave a comment

Taylor Welsh works at Plant & Food Research as part of it’s Biosecurity Research Group. Taylor’s work includes bee and pollination based research in Entomology and Embedded Systems .

Taylor is currently working towards a master’s degree in Electrical Engineering based at the University of Canterbury where he previously completed his BSc in Biochemistry and Molecular Biology.

Taylor and colleagues from Plant & Food Research and the University of California have developed a way to automate insect trap checking. They measure the wingbeat of an insect as it enters a monitoring (pheromone) trap and are building a library of data for relevant insects for the Asia Pacific region. The technology will hopefully reduce the need to manually check the thousands of traps used for biosecurity.

You can hear and discuss this with Taylor at LandWISE 2018 in Havelock North on 23-24 May.

 

 

Agronomy, AgTech, Conference, LandWISE People, Plant Health, Precision Agriculture, Research, Sensing

Sarah Pethybridge

Assistant Prof Sarah Pethybridge‘s career spans from Tasmania, through Plant & Food Research in New Zealand to Cornell University in New York. She has a focus on vegetable disease management, and a goal to provide reliable information to vegetable growers and industry stakeholders to encourage adoption of durable management strategies and tactics.

A LandWISE keynote presenter, she described leading techniques and technologies to help optimise control tools and reduce the frequency of false positive or negative decisions.

Sarah told us, “We are now in the second year of our project with the center for imaging science at Rochester Institute of Technology looking at hyperspectral data to detect flowering in snap bean to optimize timing of fungicides, and using canopy density as a risk factor. We are also expanding this work into beets to detect and differentiate abiotic and biotic stress. In the digital agriculture arena, we recently released three apps on disease detection, quantification, and spatial analysis of epidemics using pixelated data.”

Sarah’s travel to New Zealand is supported by Cornell University,  McCain Foods, Heinz-Wattie and AGMARDT

 

              

Many thanks to AGMARDT, sponsors of our international presenters 

 

Agronomy, AgTech, Conference, Data Analytics, LandWISE People, Nutrients, Plant Health, Precision Agriculture, Sensing, Soil

Michael Nichols

Michael and Rochelle Nichols and their six children have a mixed farming enterprise at Sisters Creek in Northwest Tasmania.

The family crops Wheat, Pyrethrum, Poppies, Potatoes, Onions, Canola, Mustard, Peas, Buckwheat and run 80 Friesian steers. Michael has a contracting business which provides muck spreading, spraying and combine harvesting through which he buys local wheat and barley to on sell to local dairy farmers.

The closing of a vegetable processing plant in the state prompted the family to diversify and invest in canola oil. The canola is cold pressed and sold in cubes or bottled for retail sales. 

“The oil business is ticking along nicely.  We’re providing chickens with canola meal and the cold pressed canola oil is going mostly to the Japanese catering market, as they prefer the GM-free status. We go through about 120 tonnes of seed a year and produce roughly 50,000 litres of oil.”

Michael is a very passionate farmer and is using NDVI images to improve and even up crop yields with variable rate spreader applications and is verifying the results using yield data.

Michael is an invited international presenter at LandWISE 2018

Michael’s attendance at LandWISE 2018 was supported by AGMARDT

AgTech, events, Plant Health, Research

Field day – mesh crop covers for insect and blight control on potatoes

Leave a comment

Tuesday 14 March 9.00 am – 11.00 am

FAR field site, North West corner of Springs and Ellesmere Junction Roads, Lincoln Google map.  Access off Springs Road, 300 m north of Roundabout.

Join FAR, Potatoes NZ, and the BHU Future Farming Centre for a roundup of results to date on the use of mesh crop covers for potato pest & disease control and the findings from the current field trial. 

  • How mesh covers are controlling blight
  • Mesh and tomato potato psyllid TPP control
  • Aphids and mesh
  • Potential yield boost from mesh due to improved microclimate

Get reports from the first two years trials here

Tomato potato psyllid (TPP) (Bactericera cockerelli) arrived in New Zealand in 2006 and has proved to be a important pest in a number of solanaceae crops, including potatoes.  While insecticides have proved effective for its management, this has caused a large increase in agrichemical use which is undesirable, and this option is not available to organic growers.  A ‘non-chemical’ means of controlling TPP is therefore desirable.  Mesh crop covers are such a non-chemical control: they are akin to fly screen for crops. They are extensively used in Europe for controlling a wide range of pests on an equally wide range of crops by both organic and mainstream growers. 

 

Prior research by the FFC made the serendipitous discovery that mesh crop covers are not only an effective barrier to TPP but they are also achieving significant potato blight (Phytophthora infestans and/or Alternaria solani) control.  A correlation has been shown between a reduction in UV a & b light levels and blight and also TPP symptoms. 

As mesh can keep out a wide range of potato insect pests, including those that are resistant to insecticides, such as tuber moth, it has the potential to be a single non-chemical solution to both insect pests and blight on potatoes.  As potatoes are the 4th most important food crop globally, with more grown in the developing world than the developed world, the potential global impact in terms of reduced agrichemical use is considerable.

However, potato aphids, mostly Myzus persicae, are penetrating the mesh, even mesh that has sufficiently small holes to exclude winged (and wingless) adults.  Once inside the mesh, their populations can explode due to the absence of beneficial insects, in effect, it is an unintentional experiment on the level of biological control of aphids. 

Mesh with sufficiently small holes to exclude immature aphid instars has been tested and resulted in a second serendipitous that the fine mesh appears to be modifying the under mesh micro-climate resulting in increased yields, while also improving blight control. 
Such very fine mesh has the potential therefore to completely control all potato insect pests, as well as blight and increase yield through entirely physical means. 

The field day will provide an opportunity to hear more about the research as well as viewing mesh on potatoes.

   

Agronomy, AgTech, Drainage, MicroFarm, Plant Health, Precision Agriculture, Projects, Research, Sensing, Soil, Water

Benchmarking Onion Variability 2016-17

Now in year two of our OnionsNZ SFF project, we have trials at the MicroFarm and monitoring sites at three commercial farms in Hawke’s Bay and three more in Pukekohe.

2015-16

A summary of Year 1 is on our website. A key aspect was testing a range of sensors and camera systems for assessing crop size and variability. Because onions are like needles poking from the ground, all sensors struggled especially when plants were small. This is when we want to know about the developing crop, as it is the time we make decisions and apply management.

By November our sensing was more satisfactory. At this stage we captured satellite, UAV, smartphone and GreenSeeker data and created a series of maps. 

We used the satellite image  to create canopy maps and identify zones. We sampled within the zones at harvest, and used the raltioship between November canopy and February yield to create yield maps and profit maps.

Yield assessments show considerable variation, limits imposed by population, growth of individual plants, or both

We also developed relationships between photographs of ground cover, laboratory measurements of fresh weight and leaf area and the final crop yield.

In reviewing the season’s worth of MicroFarm plot measurements and noticed there were areas where yield reached its potential, areas where yield was limited by population (establishment), some where yield was limited by canopy growth (development) and some by both population and development.

This observation helped us form a concept of Management Action Zones, based on population and canopy development assessments.

Management Action Zones – If population is low work for better establishment next season. If plants are small see if there is something that can be done this season

2016-17

Our aims for Year 2 are on the website. We set out to confirm the relationships we found in Year 1.

This required developing population expectations and determining estimates of canopy development as the season progressed, against which field measurement could be compared.

We had to select our “zones” before the crop got established as we did a lot of base line testing of the soil. So our zones were chosen based on paddock history and a fair bit of guess work. Really, we need to be able to identify zones within an establishing or developing crop, then determine what is going on so we can try to fix it as quickly as possible.

In previous seasons we experimented with smartphone cameras and image processing to assess canopy size and relate that to final yields. We are very pleased that photographs of sampling plots processed using the “Canopeo” app compare very well with Leaf Area Index again this season.

Through the season we tracked crop development in the plots and using plant counts and canopy cover assessments to try and separate the effects of population (establishment) and soil or other management factors.

We  built a web calculator to do the maths, aiming for a tool any grower or agronomist can use to aid decision making. The web calculator was used to test our theories about yield prediction and management zones.

ASL Software updated the “CoverMap” smartphone application and we obtained consistent results from it. The app calculates canopy ground cover and logs data against GPS position in real time. Because we have confidence that ground cover from image processing is closely related to Leaf Area Index we are working to turn our maps into predictions of final yields.

Maps of canopy cover created from the CoverMap smartphone application show significant variability across the paddock. Canopy increase is seen over time in two maps created a week apart

The current season’s MicroFarm crop is certainly variable. Some is deliberate: we sat the irrigator over some areas after planting to simulate heavy rain events, and we have a poorly irrigated strip. We know some relates to different soil and cover crop histories.

But some differences are unexpected and so far reasons unexplained.

Wide variation within the area new to onions does not follow artificial rain or topographic drainage patterns. This photo is of the area shown far right in the cover maps above.

Together with Plant and Food Research we have been taking additional soil samples to try and uncover the causes of patchiness.

We’ve determined one factor is our artificial rain storm, some crop loss is probably runoff from that and some is historic compaction.  We’ve even identified where a shift in our GPS AB line has left 300mm strips of low production where plants are on last year’s wheel tracks!

But there is a long way to go before this tricky crop gives up its secrets.

This project is in collaboration with Plant and Food Research and is funded by OnionsNZ and the MPI Sustainable Farming Fund.

We also appreciate the support of growers, seed companies and our MicroFarm sponsors Ballance AgriNutrients, BASF Crop Protection and the Centre for Land and Water.


 

Agronomy, Drainage, Irrigation, MicroFarm, Plant Health, Planting, Precision Agriculture, Projects, Research, Soil, Water

Onion Crop Development

Leave a comment

The crop at the MicroFarm is showing increasing variability.  The cause of some is understood, essentially excessive water pre-germination.  But in some poor performing areas the causes have yet to be determined.

The effect of our artificially applied rain event pre-emergence is clearly evident in late November.

The lasting effect of a heavy (artificial) rain event pre-emergence (right panel) shows low population and poor growth compared to areas without heavy rain (left panel)
The lasting effect of a heavy (artificial) rain event pre-emergence (right panel) shows low population and poor growth compared to areas without heavy rain (left panel)

However, we also see other areas that have poor crop development that are outside the area irrigated to create the artificial rain event.

Wide variation within the area new to onions does not follow artificial rain or topographic drainage patterns.
Wide variation within the area new to onions does not follow artificial rain or topographic drainage patterns.

Sharp differences in crop growth are evident in the new onion ground. Some parts that were heavily irrigated to simulate heavy rain show reasonable development. Areas that were not irrigated also show good development, but in some patches total crop loss.

Investigations of soil physical properties in these different areas are underway.

Agronomy, AgTech, Automation, Irrigation, MicroFarm, Nutrients, Plant Health, Precision Agriculture, Projects, Research, Sensing, Soil

Onion Crop Research Plan

Leave a comment

After identifying areas within paddocks that had yields limited by different probably causes, we conceived the idea of Management Action Zones (MAZs).

Yield assessments show considerable variation, limits imposed by population, growth of individual plants, or both
Yield assessments show considerable variation, limits imposed by population, growth of individual plants, or both

Some areas showed that yield was limited by plant number: establishment was poor. Others had the expected population, but low biomass: the plants were small due to some other limiting factor.

If we can identify zones easily, and determine the causes, we should be able to target a management response accordingly. So for this season, we set out a revised research aim.

What we want to know:

  • Can we successfully determine a management action zone in a field?

Why do we need to know this?

  • Develop a tool to increase uniformity and yield outcomes
  • Develop a tool to evaluate management practices and crop productivity

If we want to successfully determine a management action zone in a field then there are two main steps to achieve in this year’s work:

  • Confirm the relationship between digital data and crop model parameters
    • Does the relationship stay constant over time and sites?
    • How early in growth can a difference be detected?
    • Can the relationship be used to show a growth map across a field?
  • Develop an approach to gather information and ways to input and display results, initially using a website approach.
    • Can we integrate a plant count and yield information to start developing a management action zone?
    • How should this be put together in a way growers can start to use to gather information about their crops?

At the MicroFarm, we established six research zones based on paddock history and excessive wetness at establishment.

We have three paddock histories: two years of onion production with autumn cover crops of Caliente mustard, two years of onion production with autumn cover crops of oats, and no previous onion crops planted after previous summer sweetcorn and autumn sown rye grass. In each of these areas, we deliberately created sub-zones  by applying about 45mm of spray irrigation as a “large rain event”.

Artificial heavy rain event applied after planting and before emergence
Artificial heavy rain event applied after planting and before emergence

The impact of the artificial rainstorm is evident on images taken at the end of November.

The lasting effect of a heavy (artificial) rain event pre-emergence (right panel) shows low population and poor growth compared to areas without heavy rain (left panel)
The lasting effect of a heavy (artificial) rain event pre-emergence (right panel) shows low population and poor growth compared to areas without heavy rain (left panel)
AgTech, Plant Health, Research, Sensing

Vision System for Onion Crops

Leave a comment

Effective Sensing for Robotic Tasks- Still a Challenge

Chee Kit Wong

Kit Wong
Callaghan Innovation

 

Effective and reliable sensing for the performance of robotic tasks, such as manipulation in the outdoor environment remains a challenging problem.

While commercially available solutions such as ASA-LIFT are available for specific tasks and crops, and for operation in specific conditions, the systems are either not cost effective and or physically unsuitable for specific farming conditions and practices.

This research proposed to develop a mobile robot system with flexibility to adapt and with intelligence to cope with natural variability; through a two-fold aim utilising vision for navigation and manipulation. This talk discussed some of the recent developments on these aspects.

In particular, the talk focused on a novel approach that analyses point cloud information from a time-of-flight (ToF) camera to identify the location of foremost spring onions along the crop bed, for the intention of robotic manipulation. The process uses a combination of 2D image processing on the amplitude data, as well as 3D spatial analysis, extracted from the camera to locate the desired object.

Whilst the experimental results demonstrated the robustness of this approach, further testing was required to determine the ability of a system to cope with different scenarios that exist in the naturally varying environment.

For validation, the vision system was integrated with a robotic manipulation system and initial results of the investigation were presented.